This commit introduced a cyclic dependency:
Memref dialect depends on Standard because it used ConstantIndexOp.
Std depends on the MemRef dialect in its EDSC/Intrinsics.h
Working on a fix.
This reverts commit 8aa6c3765b.
Create the memref dialect and move several dialect-specific ops without
dependencies to other ops from std dialect to this dialect.
Moved ops:
AllocOp -> MemRef_AllocOp
AllocaOp -> MemRef_AllocaOp
DeallocOp -> MemRef_DeallocOp
MemRefCastOp -> MemRef_CastOp
GetGlobalMemRefOp -> MemRef_GetGlobalOp
GlobalMemRefOp -> MemRef_GlobalOp
PrefetchOp -> MemRef_PrefetchOp
ReshapeOp -> MemRef_ReshapeOp
StoreOp -> MemRef_StoreOp
TransposeOp -> MemRef_TransposeOp
ViewOp -> MemRef_ViewOp
The roadmap to split the memref dialect from std is discussed here:
https://llvm.discourse.group/t/rfc-split-the-memref-dialect-from-std/2667
Differential Revision: https://reviews.llvm.org/D96425
Currently, vector.contract joins the intermediate result and the accumulator
argument (of ranks K) using summation. We desire more joining operations ---
such as max --- to help vector.contract express reductions. This change extends
Vector_ContractionOp to take an optional attribute (called "kind", of enum type
CombiningKind) specifying the joining operation to be add/mul/min/max for int/fp
, and and/or/xor for int only. By default this attribute has value "add".
To implement this we also need to extend vector.outerproduct, since
vector.contract gets transformed to vector.outerproduct (and that to
vector.fma). The extension for vector.outerproduct is also an optional kind
attribute that uses the same enum type and possible values. The default is
"add". In case of max/min we transform vector.outerproduct to a combination of
compare and select.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D93280
Align the vector gather/scatter/expand/compress API with
the vector load/store/maskedload/maskedstore API.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D96396
This patch adds the 'vector.load' and 'vector.store' ops to the Vector
dialect [1]. These operations model *contiguous* vector loads and stores
from/to memory. Their semantics are similar to the 'affine.vector_load' and
'affine.vector_store' counterparts but without the affine constraints. The
most relevant feature is that these new vector operations may perform a vector
load/store on memrefs with a non-vector element type, unlike 'std.load' and
'std.store' ops. This opens the representation to model more generic vector
load/store scenarios: unaligned vector loads/stores, perform scalar and vector
memory access on the same memref, decouple memory allocation constraints from
memory accesses, etc [1]. These operations will also facilitate the progressive
lowering of both Affine vector loads/stores and Vector transfer reads/writes
for those that read/write contiguous slices from/to memory.
In particular, this patch adds the 'vector.load' and 'vector.store' ops to the
Vector dialect, implements their lowering to the LLVM dialect, and changes the
lowering of 'affine.vector_load' and 'affine.vector_store' ops to the new vector
ops. The lowering of Vector transfer reads/writes will be implemented in the
future, probably as an independent pass. The API of 'vector.maskedload' and
'vector.maskedstore' has also been changed slightly to align it with the
transfer read/write ops and the vector new ops. This will improve reusability
among all these operations. For example, the lowering of 'vector.load',
'vector.store', 'vector.maskedload' and 'vector.maskedstore' to the LLVM dialect
is implemented with a single template conversion pattern.
[1] https://llvm.discourse.group/t/memref-type-and-data-layout/
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D96185
This reverts commit 511dd4f438 along with
a couple fixes.
Original message:
Now the context is the first, rather than the last input.
This better matches the rest of the infrastructure and makes
it easier to move these types to being declaratively specified.
Phabricator: https://reviews.llvm.org/D96111
Now the context is the first, rather than the last input.
This better matches the rest of the infrastructure and makes
it easier to move these types to being declaratively specified.
Differential Revision: https://reviews.llvm.org/D96111
This ensures the memref base + indices expression is well-formed
Reviewed By: ThomasRaoux, ftynse
Differential Revision: https://reviews.llvm.org/D94441
This allow more accurate modeling of the side effects and allow dead code
elimination to remove dead transfer ops.
Differential Revision: https://reviews.llvm.org/D94318
This change makes the scatter/gather syntax more consistent with
the syntax of all the other memory operations in the Vector dialect
(order of types, use of [] for index, etc.). This will make the MLIR
code easier to read. In addition, the pass_thru parameter of the
gather has been made mandatory (there is very little benefit in
using the implicit "undefined" values).
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D94352
Adding the ability to index the base address brings these operations closer
to the transfer read and write semantics (with lowering advantages), ensures
more consistent use in vector MLIR code (easier to read), and reduces the
amount of code duplication to lower memrefs into base addresses considerably
(making codegen less error-prone).
Reviewed By: ThomasRaoux
Differential Revision: https://reviews.llvm.org/D94278
Implement Bug 46698, making ODS synthesize a getType() method that returns a
specific C++ class for OneResult methods where we know that class. This eliminates
a common source of casts in things like:
myOp.getType().cast<FIRRTLType>().getPassive()
because we know that myOp always returns a FIRRTLType. This also encourages
op authors to type their results more tightly (which is also good for
verification).
I chose to implement this by splitting the OneResult trait into itself plus a
OneTypedResult trait, given that many things are using `hasTrait<OneResult>`
to conditionalize various logic.
While this changes makes many many ops get more specific getType() results, it
is generally drop-in compatible with the previous behavior because 'x.cast<T>()'
is allowed when x is already known to be a T. The one exception to this is that
we need declarations of the types used by ops, which is why a couple headers
needed additional #includes.
I updated a few things in tree to remove the now-redundant `.cast<>`'s, but there
are probably many more than can be removed.
Differential Revision: https://reviews.llvm.org/D93790
Transfer_ops can now work on both buffers and tensor. Right now, lowering of
the tensor case is not supported yet.
Differential Revision: https://reviews.llvm.org/D93500
This better matches the rest of the infrastructure, is much simpler, and makes it easier to move these types to being declaratively specified.
Differential Revision: https://reviews.llvm.org/D93432
Given that OpState already implicit converts to Operator*, this seems reasonable.
The alternative would be to add more functions to OpState which forward to Operation.
Reviewed By: rriddle, ftynse
Differential Revision: https://reviews.llvm.org/D92266
These includes have been deprecated in favor of BuiltinDialect.h, which contains the definitions of ModuleOp and FuncOp.
Differential Revision: https://reviews.llvm.org/D91572
motivated by a refactoring in the new sparse code (yet to be merged), this avoids some lengthy code dup
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D91465
Support multi-dimension vector for InsertMap/ExtractMap op and update the
transformations. Currently the relation between IDs and dimension is implicitly
deduced from the types. We can then calculate an AffineMap based on it. In the
future the AffineMap could be part of the operation itself.
Differential Revision: https://reviews.llvm.org/D90995
Based on discourse discussion, fix the doc string and remove examples with
wrong semantic. Also fix insert_map semantic by adding missing operand for
vector we are inserting into.
Differential Revision: https://reviews.llvm.org/D89563
Add folder for the case where ExtractStridedSliceOp source comes from a chain
of InsertStridedSliceOp. Also add a folder for the trivial case where the
ExtractStridedSliceOp is a no-op.
Differential Revision: https://reviews.llvm.org/D89850
Combine ExtractOp with scalar result with BroadcastOp source. This is useful to
be able to incrementally convert degenerated vector of one element into scalar.
Differential Revision: https://reviews.llvm.org/D88751
While affine maps are part of the builtin memref type, there is very
limited support for manipulating them in the standard dialect. Add
transpose to the set of ops to complement the existing view/subview ops.
This is a metadata transformation that encodes the transpose into the
strides of a memref.
I'm planning to use this when lowering operations on strided memrefs,
using the transpose to remove the stride without adding a dependency on
linalg dialect.
Differential Revision: https://reviews.llvm.org/D88651
Add basic canonicalization patterns for the extractMap/insertMap to allow them
to be folded into Transfer ops.
Also mark transferRead as memory read so that it can be removed by dead code.
Differential Revision: https://reviews.llvm.org/D88622
This is the first of several steps to support distributing large vectors. This
adds instructions extract_map and insert_map that allow us to do incremental
lowering. Right now the transformation only apply to simple pointwise operation
with a vector size matching the multiplicity of the IDs used to distribute the
vector.
This can be used to distribute large vectors to loops or SPMD.
Differential Revision: https://reviews.llvm.org/D88341
Recently, restrictions on vector reductions were made more relaxed by
accepting any width signless integer and floating-point. This CL relaxes
the restriction even more by including unsigned and signed integers.
Reviewed By: bkramer
Differential Revision: https://reviews.llvm.org/D88442
Fold the operation if the source is a scalar constant or splat constant.
Update transform-patterns-matmul-to-vector.mlir because the broadcast ops are folded in the conversion.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D87703
Now backends spell out which namespace they want to be in, instead of relying on
clients #including them inside already-opened namespaces. This also means that
cppNamespaces should be fully qualified, and there's no implicit "::mlir::"
prepended to them anymore.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D86811
Vector to SCF conversion still had issues due to the interaction with the natural alignment derived by the LLVM data layout. One traditional workaround is to allocate aligned. However, this does not always work for vector sizes that are non-powers of 2.
This revision implements a more portable mechanism where the intermediate allocation is always a memref of elemental vector type. AllocOp is extended to use the natural LLVM DataLayout alignment for non-scalar types, when the alignment is not specified in the first place.
An integration test is added that exercises the transfer to scf.for + scalar lowering with a 5x5 transposition.
Differential Revision: https://reviews.llvm.org/D87150
Masked loading/storing in various forms can be optimized
into simpler memory operations when the mask is all true
or all false. Note that the backend does similar optimizations
but doing this early may expose more opportunities for further
optimizations. This further prepares progressively lowering
transfer read and write into 1-D memory operations.
Reviewed By: ThomasRaoux
Differential Revision: https://reviews.llvm.org/D85769
This patch moves the registration to a method in the MLIRContext: getOrCreateDialect<ConcreteDialect>()
This method requires dialect to provide a static getDialectNamespace()
and store a TypeID on the Dialect itself, which allows to lazyily
create a dialect when not yet loaded in the context.
As a side effect, it means that duplicated registration of the same
dialect is not an issue anymore.
To limit the boilerplate, TableGen dialect generation is modified to
emit the constructor entirely and invoke separately a "init()" method
that the user implements.
Differential Revision: https://reviews.llvm.org/D85495
